Are you a data packrat? Does your business keep and receive an enormous amount of data? If so, do you just stuff it somewhere and hope to figure out what to do with it some day? 70% of the battle with Big Data is making it manageable so that it can then be meaningful to you. Business insight and valuable intelligence remain buried on disks and tapes unless you have a way to making access…

I was recently discussing a Big Data initiative with a British financial services organization. They had made significant investments in their infrastructure and now wanted ‘to fill up’ their Big Data lake. The DataSift platform is a Big Data platform that processes over 2.1bn unique items of unstructured human-generated data every day. The interesting way the client phrased their objective made me think about ways to measure volume when working with social and news data….

Humans are social creatures. That might even be truer when we go online. Consider the following recent (beginning portion of 2014) statistics about the most popular social network and blog platforms and their memberships: Twitter has 560 million registered users, and over half of them are active, and at least as of a couple of years ago, there were 200 million tweets sent every single day. WordPress powers 20% of the top global sites and…

In our latest of use case posts, we will look at two brands – Home Depot and Lowes – and compare their share of voice. Does one brand have more social presence than the other? Does one brand outperform the other in terms of volume or hashtag and mention usage? How do they compare geographically? Here’s a simple, end-to-end scenario for collecting, consuming and analyzing DataSift data to discover your share of voice. Let’s find…

During the past decade, few business buzzwords/terms have had as much success as ‘Big Data’. It’s graced the covers of business magazines, been the central topic of an endless number of conferences, and helped countless tech folks explain to their families what they do for a living. In this blog post I’d like to propose a new way at looking at ‘Big Data’ given the changing nature of data in organizations that addresses an inherent…

Every Month: More than 400 million people read 15+ billion WordPress blogs 1.4 billion people read comments on the DISQUS platform across 3 million sites People see more than 250 million Tumblr posts … not to mention countless readers of other boards and blogs across the web How Is This Content Affecting Your Business? Digital and social channels have created a huge opportunity for businesses to tap into the thoughts, emotions, intentions and opinions of…

If in the past you’ve tried to get data from social networks, you’ll be familiar with the pains of constantly changing APIs, moving data schemas, frequent policy changes. If you’re attempting to work with multiple networks, you’ll be hitting these challenges time and time again. You’ll have wasted weeks of development time just reacting to changes. DataSift’s API gives you a consistent, supported, flexible platform that allows you to confidently & quickly deliver social solutions….

From support to HR or product, a company’s online community contains a wealth of good ideas to improve a business. There are dozens if not hundreds of valuable people who actively participate in them. But with such a volume of content and only so much time, how do you get a birds eye view of it all? What’s the best way to pinpoint the ideas and people that really matter within your online community? DataSift…

DataSift has just announced our integration with Informatica’s PowerExchange, enabling global organizations to bridge social and news data into the enterprise and merge it with proprietary data living in their MDM systems, creating a true 360-degree view of their businesses. What potential does this unlock for your company?

To start things off, I’d like to introduce Sifting Around, a new series where I’ll demonstrate the analytics process I use when exploring a current event from a social data perspective. From writing a CSDL script to creating visualizations, I’ll give you the how and why behind each step and highlight different DataSift enrichments that I found particularly useful. Conclusions drawn here are entirely my own and are guaranteed by no one, nor is any…